“Anant Madabhushi”的意思、由来-开放百科全书

Madabhushi has over 75 patents either issued or pending in the areas of medical image analysis, computer-aided diagnosis, and computer vision.^[2] and currently holds 24 patents in medical imaging analysis, computer vision and computer-aided diagnosis. In 2017, he was awarded patents for “Histogram of hosoya index (HoH) features for quantitative histomorphometry)”^[3] and “Textural analysis of lung nodules.”^[4]

The author of hundreds of peer-reviewed journal articles and conference papers, Madabhushi is a sought after lecturer who has delivered more than 180 talks around the world. His efforts as a professor and researcher have gained international attention in the field of biomedical engineering, garnering him several awards. Most notably, Madabhushi is a Wallace H. Coulter Fellow and a fellow of the American Institute of Medical and Biomedical Engineering (AIMBE). In 2015, he made Crain’s Business Cleveland magazine’s “Forty under 40” list.^[5] He also was the recipient of an Early Career Lung Cancer Grant from the Department of Defense in 2014 and an Early Career Award from the Society of Imaging Informatics in Medicine (SIIM) in 2009.^[6]

Education

Madabhushi received a bachelor's degree in biomedical engineering from Mumbai University, India in 1998 and a master's degree in biomedical engineering from the University of Texas, Austin in 2000. In 2004, he received his PhD in bioengineering from the University of Pennsylvania.^[7]

Career

Madabhushi joined the Department of Biomedical Engineering at Rutgers University as an assistant professor in 2005. He became an associate professor with tenure in 2010. In 2012, he left Rutgers and joined Case Western Reserve University’s Department of Biomedical Engineering as an associate professor. He became a full professor in 2014 and moved to the position of F. Alex Nason professor II endowed chair of biomedical engineering in 2016. Madabhushi also serves as the director of the university’s Center for Computational Imaging and Personalized Diagnostics (CCIPD).^[8]

Madabhushi is the co-founder of Ibris Inc. a startup company focused on developing image based assays for breast cancer prognosis. He was also the conference chair for the Digital Pathology Conference held in conjunction with the SPIE Medical Imaging Symposium between 2013-2016.^[9]

Publications and Conferences

Madabhushi has written more than 180 peer-reviewed journal publications, appearing in journals such as Radiology, Scientific Reports, American Journal of Surgical Pathology, the Annual Review of Biomedical Engineering, Medical Image Analysis, IEEE Transactions on Medical Imaging and PLOS One. He has authored over 150 papers for conferences including SPIE Medical Imaging, the Medical Image Computing and Computer Assisted Intervention (MICCAI) Conference and the International Symposium on Biomedical Imaging (ISBI).^[10]

Madabhushi has delivered over 240 invited talks and lectures in the United States and abroad. He is an Associate Editor for IEEE Transactions on Biomedical Engineering, IEEE Transactions on Biomedical Engineering Letters, BMC Cancer, BMC Medical Imaging, the Journal of Medical Imaging and Medical Image Analysis (MedIA). He also serves on the editorial board of Analytical Cellular Pathology.

Awards and memberships

Madabhushi has over 75 patents either issued or pending in the areas of medical image analysis, computer-aided diagnosis and computer vision. In March 2017, he was issued a patent for “Textural analysis of lung nodules”^[11] covering methods and apparatus for classifying a region of tissue using textural analysis so a patient prognosis can be made based on the classification of the image. In January 2017, he was issued a patent for “Histogram of hosoya index (HoH) features for quantitative histomorphometry),”^[12] an invention that captures cancer architecture in digital pathology images and can help differentiate between more and less aggressive early stage, estrogen receptor positive breast cancers.

Madabhushi has received the Department of Defense New Investigator Award in Lung Cancer (2014); The Excellence in Teaching Award (2007-2009) from Rutgers University; and the Coulter Phase 1 and Phase 2 Early Career award (2006, 2008).^[13]

In 2015, Madabhushi was named one of the “Forty under 40” people making a positive impact on business in northeast Ohio by Crain’s Cleveland Business magazine. He is a Wallace H. Coulter Fellow, a Fellow of the American Institute of Medical and Biological Engineering (AIMBE) and a Senior IEEE member. He has also served or serves as an Associate Editor for IEEE Transactions on Biomedical Engineering, IEEE Transactions on Biomedical Engineering Letters, BMC Cancer, BMC Medical Imaging, Journal of Medical Imaging and Medical Image Analysis (MedIA). He is also on the Editorial Board of the Journal Analytical and Cellular Pathology.^[14]

Research

Madabhushi is director of Case Western Reserve University’s Center for Computational Imaging and Personalized Diagnostics (CCIPD). His team at the CCIPD is developing image analysis, statistical pattern recognition, machine learning and artificial intelligence tools to computationally interrogate biomedical image data, including MRI, CAT scans and digital pathology tissue images. The tools can be used to predict disease progression and provide a score to clinicians on the aggressiveness of a patient’s disease, such as breast cancer and prostate cancer, which can in turn help physicians decide on appropriate treatment options.^[15]

The impetus for the CCIPD’s systems-based approach to disease understanding is to diverge from a traditional approach of focusing on a limited number of molecular components to a broader understanding of how numerous interrelated health variables – proteomics, metabolites, genomics – result in the emergence of definable phenotypes. Work done under Madabhushi’s guidance has yielded results, including the discovery of computationally-derived image biomarkers that pave the way for disease prognosis, thereby allowing physicians to predict which patient may be susceptible to a specific disease and also predict disease outcome and survival.^[16]^[17] In addition, research on image biomarkers is being applied by the CCIPD group to the field of “radiogenomics”^[18] or predicting the mutational status or molecular subtype^[19] of a tumor based solely off computational features derived from a routine imaging scan. Dr. Madabhushi’s team also has pioneered the Ibris (image based risk score),^[20] which computes the probability of disease aggressiveness using features mined from medical images for a variety of cancers.^[21]^[22]^[23]^[24]

Madabhushi’s research has received grant funding from the National Cancer Institute (NIH), National Science Foundation, the Department of Defense, private foundations and industry.

References

1. ^http://engineering.case.edu/centers/ccipd/
2. ^{{Cite web|url=http://patents.justia.com/inventor/anant-madabhushi|title=Anant Madabhushi Inventions, Patents and Patent Applications - Justia Patents Search|website=patents.justia.com|language=en|accessdate=2017-05-19}}
3. ^{{Citation|title=United States Patent: 9558394 - Histogram of hosoya index (HoH) features for quantitative histomorphometry|date=January 31, 2017|url=http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PALL&p=1&u=/netahtml/PTO/srchnum.htm&r=1&f=G&l=50&s1=9558394.PN.&OS=PN/9558394&RS=PN/9558394|inventor-last=Madabhushi|inventor2-last=Basavanhally|inventor3-last=Ali|inventor-first=Anant|inventor2-first=Ajay|inventor3-first=Sahirzeeshan|issue=9558394|accessdate=2017-05-19}}
4. ^{{Citation|title=United States Patent: 9595103 - Textural analysis of lung nodules|date=March 14, 2017|url=http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PALL&p=1&u=/netahtml/PTO/srchnum.htm&r=1&f=G&l=50&s1=9595103.PN.&OS=PN/9595103&RS=PN/9595103|inventor-last=Madabhushi|inventor2-last=Rusu|inventor3-last=Orooji|inventor-first=Anant|inventor2-first=Mirabela|inventor3-first=Mahdi|issue=9595103|accessdate=2017-05-19}}
5. ^{{Cite news|url=http://www.crainscleveland.com/article/20151121/FORTY15/151129950/anant-madabhushi-39|title=Anant Madabhushi, 39|date=2015-11-21|work=Crain's Cleveland Business|accessdate=2017-05-19|language=en}}
6. ^{{Cite web|url=http://engineering.case.edu/ebme/CCIPD-Spring-2018-Funding|title=Funding Rolls in for Computational Imaging Research {{!}} Department of Biomedical Engineering|website=engineering.case.edu|language=en|access-date=2018-09-13}}
7. ^{{Cite web|url=https://case.edu/medicine/ccir/faculty/anant-madabhushi-phd.html|title=Faculty - Case Center for Imaging Research - Case Western Reserve University|website=case.edu|language=en|accessdate=2017-05-19}}
8. ^{{Cite web|url=https://www.linkedin.com/in/anant-madabhushi-9a75a21/|title=Anant Madabhushi|last=Madabhushi|first=Anant|date=May 19, 2017|website=LinkedIn |archiveurl= |archivedate= |deadurl= |accessdate=May 19, 2017}}
9. ^{{Cite web|url=https://bme.rutgers.edu/news/madabhushi-ibris-inc-awarded-207k-phase-1-sbir-award-nibib|title=Madabhushi, Ibris Inc. awarded 207K Phase 1 SBIR award from NIBIB {{!}} Rutgers University, Biomedical Engineering|website=bme.rutgers.edu|access-date=2019-01-25}}
10. ^{{Cite web|url=https://www.ncbi.nlm.nih.gov/pubmed/?term=anant+madabhushi|title=anant madabhushi - PubMed - NCBI|last=pubmeddev|website=www.ncbi.nlm.nih.gov|language=en|access-date=2018-10-11}}
11. ^{{Citation|title=Textural Analysis of Lung Nodules|date=June 2, 2016|url=http://www.google.com/patents/US20160155225|inventor-last=Madabhushi|inventor2-last=Rusu|inventor3-last=Orooji|inventor-first=Anant|inventor2-first=Mirabela|inventor3-first=Mahdi|issue=US20160155225 A1|accessdate=2017-05-19}}
12. ^{{Citation|title=Histogram of Hosoya Index (HoH) Features For Quantitative Histomorphometry|date=September 10, 2015|url=http://www.google.com/patents/US20150254494|inventor-last=Madabhushi|inventor2-last=Basavanhally|inventor3-last=Ali|inventor-first=Anant|inventor2-first=Ajay|inventor3-first=Sahirzeeshan|issue=US20150254494 A1|accessdate=2017-05-19}}
13. ^{{Cite web|url=http://mlmi2017.web.unc.edu/keynote-speaker/|title=8th International Workshop on Machine Learning in Medical Imaging|last=|first=|date=September 13, 2018|website=|archive-url=http://mlmi2017.web.unc.edu/keynote-speaker/|archive-date=September 10, 2017|dead-url=|access-date=September 13, 2018}}
14. ^{{Cite web|url=http://engineering.case.edu/profiles/axm788|title=CSE Faculty/Staff Profiles|website=engineering.case.edu|language=en|accessdate=2017-05-19}}
15. ^{{Cite web|url=http://engineering.case.edu/centers/ccipd/|title=Center for Computational Imaging and Personalized Diagnostics|website=engineering.case.edu|language=en|accessdate=2017-05-19}}
16. ^{{Cite journal|last=Madabhushi|first=Anant|last2=Agner|first2=Shannon|last3=Basavanhally|first3=Ajay|last4=Doyle|first4=Scott|last5=Lee|first5=George|date=2011-10-01|title=Computer-aided prognosis: predicting patient and disease outcome via quantitative fusion of multi-scale, multi-modal data|journal=Computerized Medical Imaging and Graphics|volume=35|issue=7-8|pages=506–514|doi=10.1016/j.compmedimag.2011.01.008|issn=1879-0771|pmid=21333490}}
17. ^{{Cite journal|last=Madabhushi|first=Anant|last2=Agner|first2=Shannon|last3=Basavanhally|first3=Ajay|last4=Doyle|first4=Scott|last5=Lee|first5=George|date=2011-10-01|title=Computer-aided prognosis: predicting patient and disease outcome via quantitative fusion of multi-scale, multi-modal data|journal=Computerized Medical Imaging and Graphics|volume=35|issue=7-8|pages=506–514|doi=10.1016/j.compmedimag.2011.01.008|issn=1879-0771|pmid=21333490}}
18. ^{{Cite journal|last=Wan|first=Tao|last2=Bloch|first2=B. Nicolas|last3=Plecha|first3=Donna|last4=Thompson|first4=CheryI L.|last5=Gilmore|first5=Hannah|last6=Jaffe|first6=Carl|last7=Harris|first7=Lyndsay|last8=Madabhushi|first8=Anant|date=2016-02-18|title=A Radio-genomics Approach for Identifying High Risk Estrogen Receptor-positive Breast Cancers on DCE-MRI: Preliminary Results in Predicting OncotypeDX Risk Scores|journal=Scientific Reports|volume=6|doi=10.1038/srep21394|issn=2045-2322|pmc=4757835|pmid=26887643}}
19. ^{{Cite journal|last=Agner|first=Shannon C.|last2=Rosen|first2=Mark A.|last3=Englander|first3=Sarah|last4=Tomaszewski|first4=John E.|last5=Feldman|first5=Michael D.|last6=Zhang|first6=Paul|last7=Mies|first7=Carolyn|last8=Schnall|first8=Mitchell D.|last9=Madabhushi|first9=Anant|date=2017-05-19|title=Computerized Image Analysis for Identifying Triple-Negative Breast Cancers and Differentiating Them from Other Molecular Subtypes of Breast Cancer on Dynamic Contrast-enhanced MR Images: A Feasibility Study|journal=Radiology|volume=272|issue=1|pages=91–99|doi=10.1148/radiol.14121031|issn=0033-8419|pmc=4263619|pmid=24620909}}
20. ^{{Cite journal|last=Ganesan|first=S.|last2=Madabhushi|first2=A.|last3=Basavanhally|first3=A.|last4=Xu|first4=J.|last5=Bhanot|first5=G.|last6=Barnard|first6=N.|last7=Toppmeyer|first7=D.|date=2009-12-15|title=Computerized Histologic Image-Based Risk Score (IbRiS) Classifier for ER+ Breast Cancer.|url=http://cancerres.aacrjournals.org/content/69/24_Supplement/3046|journal=Cancer Research|language=en|volume=69|issue=24 Supplement|pages=3046–3046|doi=10.1158/0008-5472.SABCS-09-3046|issn=0008-5472}}
21. ^{{Cite journal|last=Lewis|first=James S.|last2=Ali|first2=Sahirzeeshan|last3=Luo|first3=Jingqin|last4=Thorstad|first4=Wade L.|last5=Madabhushi|first5=Anant|date=2017-05-19|title=A Quantitative Histomorphometric Classifier (QuHbIC) Identifies Aggressive Versus Indolent p16-Positive Oropharyngeal Squamous Cell Carcinoma|journal=The American Journal of Surgical Pathology|volume=38|issue=1|pages=128–137|doi=10.1097/PAS.0000000000000086|issn=0147-5185|pmc=3865861|pmid=24145650}}
22. ^{{Cite journal|last=Lee|first=George|last2=Sparks|first2=Rachel|last3=Ali|first3=Sahirzeeshan|last4=Shih|first4=Natalie N. C.|last5=Feldman|first5=Michael D.|last6=Spangler|first6=Elaine|last7=Rebbeck|first7=Timothy|last8=Tomaszewski|first8=John E.|last9=Madabhushi|first9=Anant|date=2014-05-29|title=Co-Occurring Gland Angularity in Localized Subgraphs: Predicting Biochemical Recurrence in Intermediate-Risk Prostate Cancer Patients|url=http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0097954|journal=PLOS ONE|volume=9|issue=5|pages=e97954|doi=10.1371/journal.pone.0097954|issn=1932-6203|pmc=4038543|pmid=24875018}}
23. ^{{Cite journal|last=Basavanhally|first=Ajay|last2=Ganesan|first2=Shridar|last3=Feldman|first3=Michael|last4=Shih|first4=Natalie|last5=Mies|first5=Carolyn|last6=Tomaszewski|first6=John|last7=Madabhushi|first7=Anant|date=2013-08-01|title=Multi-field-of-view framework for distinguishing tumor grade in ER+ breast cancer from entire histopathology slides|journal=IEEE Transactions on Bio-medical Engineering|volume=60|issue=8|pages=2089–2099|doi=10.1109/TBME.2013.2245129|issn=1558-2531|pmid=23392336}}
24. ^{{Cite journal|last=Basavanhally|first=Ajay|last2=Feldman|first2=Michael|last3=Shih|first3=Natalie|last4=Mies|first4=Carolyn|last5=Tomaszewski|first5=John|last6=Ganesan|first6=Shridar|last7=Madabhushi|first7=Anant|date=2012-01-19|title=Multi-field-of-view strategy for image-based outcome prediction of multi-parametric estrogen receptor-positive breast cancer histopathology: Comparison to Oncotype DX|journal=Journal of Pathology Informatics|volume=2|doi=10.4103/2153-3539.92027|issn=2153-3539|pmc=3312707|pmid=22811953}}